Originally Posted by
Spectral
I do not see any plausible argument that teaching, nursing, social work, and child care are consistently monetarily undervalued. In the case of teaching and nursing, they both have artificially restricted labor supplies that inflate labor cost relative to what a market would drive. In the case of social work and child care, these simply aren't high skill, difficult jobs. Yes, it's important that someone do it, but in the same sense that public sanitation is critical to a functional society - that doesn't mean that it's going to command high pay.
I generally find the idea of professions being monetarily undervalued to be pretty incoherent. There isn't some arbiter of value that's setting the labor price, it's a result of the supply and demand for the type of labor. Take, for example, scientists - that's a high skill, high added value profession that nonetheless commands lowish wages. Why? Not because someone decided that science just isn't worth much, but because a lot of smart people are willing to do it without very much compensation. Sure, in some abstract sense you could argue that scientists (or teachers, or nurses, or other "good" professions) deserve more, but wages aren't about some sort of cosmic justice.
That women tend to pick professions that don't command as high of salaries says... well, something. But it doesn't say that there's a valid basis to demand the implementation of government force to level wages between professions that don't command the same pay.
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After doing so, what they find is ~7% (see Figure 10 on page 20). Notably, this doesn't mean that 7% must be attributable to discrimination, it means that the maximum possible amount that could be caused by discrimination is 7%. Attributing that 7% gap to discrimination would be to massively privilege the hypothesis while ignoring numerous possible explanations such as measurement error, a productivity gap, choices made based on family planning, small in-profession job differences that may not be accounted for in their data, preferences in the types of firms men and women work for, and so on.
Ultimately, when you have at least a dozen or so possible factors to consider for a 7% gap, the main takeaway should be that none of them probably explain much individual, including discrimination.